An In Vitro Selection Platform to Identify Multiple Aptamers against Multiple Cell-Surface Markers Using Ligand-Guided Selection

利用配体引导筛选技术,在体外筛选平台中鉴定针对多种细胞表面标志物的多种适体

阅读:6
作者:Nicole B Williams,Sana Batool,Hasan E Zumrut,Rutika Patel,German Sosa,Mohammad Jamal,Prabodhika Mallikaratchy

Abstract

Aptamer ligand discovery against multiple molecules expressed on whole cells is an essential component in molecular tool development. However, owing to their intrinsic structural characteristics, cell-surface receptors have proven to be challenging targets in ligand discovery. Several variants to systematic evolution of ligands by exponential enrichment (SELEX) have been introduced to address the ″target problem″ for aptamer screening. To this end, we introduced a variant of SELEX, termed ligand-guided selection (LIGS), to identify highly specific aptamers against complex cell-surface markers in their native state. So far, the application of LIGS has been aimed at identifying aptamers against the most dominant receptors on the cell surface. Here, we report that LIGS can be expanded to identify two receptors on the same cell surface, paving the way to generate a multiplexed ligand discovery platform based on SELEX-targeting membrane receptors in their native functional state. Using CD19 and CD20 expressed on Toledo cells as a model system, multiple aptamer families were evolved against Toledo cells. We then utilized two monoclonal antibodies (mAbs) against CD20 and CD19 to selectively partition specific aptamers against CD19 and CD20. Following biochemical characterization, we introduce two specific aptamers against CD19 and two specific aptamers against CD20 with high affinity. Multi-target LIGS, as reported here, demonstrates a successful combinatorial approach for nucleic acid library screening to generate multiple artificial nucleic acid ligands against multiple receptors expressed on a single cell.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。